Abstract
At present, there are many methods for data dimensionality reduction, but most of the results of decomposition methods allow negative values. Obviously, these negative values have no physical meaning in practical problems. The non-negative matrix factorization method is a dimensionality reduction under the condition of ensuring non-negative values. This paper mainly uses a non-negative matrix factorization algorithm to perform dimensionality reduction representation and local feature extraction of data, and then classify. Experiments show that the algorithm in this paper is reasonable and effective.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
